All mobile communication systems suffer from short-term and long-term blockage. In particular, communication systems requiring line of sight are frequently blocked. An example of short-term blockage is a tunnel. An example of a long-term blockage source is a parking garage. Blockage occurs when the loss introduced by the blockage source exceeds the link margin in the communications system. Depending on the design constraints, a variety of schemes may be used to reestablish the communications link once the blockage source is removed.
One approach is to continually monitor the communications channel, and reestablish communications as soon as the blockage source is removed. That is suitable for short-term blockage and the long-term blockage when power consumption is not important. In many mobile communications applications, however, power consumption is critical. With battery powered devices, long-term blockage could result in permanent blockage if the battery is drained due to a power hungry blockage recovery scheme.
Another approach, intended to overcome that difficulty, is called periodic monitoring. The power consumption constraint in battery-powered applications leads to less frequent monitoring of the channel. That reduces power consumption, and also increases the amount of time required to reestablish communications once the blockage source is removed. Thus, a periodic monitoring approach is not preferred.
In yet another approach, optimized periodic monitoring, one attempts to optimize the monitoring interval based on the amount of time the mobile device has been blocked. That involves monitoring the channel more frequently at first, in the hope that the blockage is only short-term, which is typically more frequent than long-term blockage. That minimizes the amount of time required to reestablish communications once the blockage source is removed for the most frequently encountered scenario. If the device has been blocked for a longer period of time, it reduces the frequency of channel monitoring in an effort to conserve power.
The aforementioned approaches can become quite sophisticated, and can make use of several possible sampling intervals in an effort to optimize the trade-off between power consumption and latency. Those schemes are often based on statistical data specific to the target application, such as long-haul trucking, for example. Having representative statistics allows the designer to optimize the blockage recovery scheme.
Despite the best efforts of the designer, there are some applications where power consumption and latency requirements are outside of the performance envelope that can be achieved using the mentioned blockage recovery schemes. Applications that have very long-term blockage, require low latency, and require low power consumption can be very challenging.
An example of such an application is container shipping. In container shipping, containers are stacked on the ship, resulting in blockage for the duration of the trip. When the ship is unloaded, the containers are often stacked once again in the shipping yard. That leaves a short interval during unloading in which to establish communications and send a report.